{"id":638159,"date":"2021-09-24T08:09:00","date_gmt":"2021-09-24T08:09:00","guid":{"rendered":"https:\/\/www.capgemini.com\/no-no\/?post_type=client-story&#038;p=638159"},"modified":"2025-03-20T03:27:01","modified_gmt":"2025-03-20T03:27:01","slug":"ars-develops-step-to-predict-hospital-bed-saturation","status":"publish","type":"client-story","link":"https:\/\/www.capgemini.com\/no-no\/news\/client-stories\/ars-develops-step-to-predict-hospital-bed-saturation\/","title":{"rendered":"ARS develops STEP to predict hospital bed saturation"},"content":{"rendered":"\n<header class=\"wp-block-cg-blocks-hero-reusable is-style-default header heroReusable  \"><div class=\"header-bgs\"><picture><source srcset=\"https:\/\/www.capgemini.com\/no-no\/wp-content\/uploads\/2021\/09\/ÎÚÑ»´«Ã½_Client-Stories_ARS-DEVELOPS-STEP-TO-PREDICT-HOSPITAL-BED-SATURATION.jpg?w=2880&amp;quality=70 1x, https:\/\/www.capgemini.com\/no-no\/wp-content\/uploads\/2021\/09\/ÎÚÑ»´«Ã½_Client-Stories_ARS-DEVELOPS-STEP-TO-PREDICT-HOSPITAL-BED-SATURATION.jpg?w=2880&amp;quality=70 2x\" media=\"(min-width: 1500px)\"\/><source srcset=\"https:\/\/www.capgemini.com\/no-no\/wp-content\/uploads\/2021\/09\/ÎÚÑ»´«Ã½_Client-Stories_ARS-DEVELOPS-STEP-TO-PREDICT-HOSPITAL-BED-SATURATION.jpg?w=1440&amp;quality=70 1x, https:\/\/www.capgemini.com\/no-no\/wp-content\/uploads\/2021\/09\/ÎÚÑ»´«Ã½_Client-Stories_ARS-DEVELOPS-STEP-TO-PREDICT-HOSPITAL-BED-SATURATION.jpg?w=2880&amp;quality=70 2x\" media=\"(min-width: 992px)\"\/><source srcset=\"https:\/\/www.capgemini.com\/no-no\/wp-content\/uploads\/2021\/09\/ÎÚÑ»´«Ã½_Client-Stories_ARS-DEVELOPS-STEP-TO-PREDICT-HOSPITAL-BED-SATURATION.jpg?w=1024&amp;quality=70 1x, https:\/\/www.capgemini.com\/no-no\/wp-content\/uploads\/2021\/09\/ÎÚÑ»´«Ã½_Client-Stories_ARS-DEVELOPS-STEP-TO-PREDICT-HOSPITAL-BED-SATURATION.jpg?w=1024&amp;quality=70 2x\" media=\"(min-width: 768px)\"\/><source srcset=\"https:\/\/www.capgemini.com\/no-no\/wp-content\/uploads\/2021\/09\/ÎÚÑ»´«Ã½_Client-Stories_ARS-DEVELOPS-STEP-TO-PREDICT-HOSPITAL-BED-SATURATION.jpg?w=768&amp;quality=70 1x, https:\/\/www.capgemini.com\/no-no\/wp-content\/uploads\/2021\/09\/ÎÚÑ»´«Ã½_Client-Stories_ARS-DEVELOPS-STEP-TO-PREDICT-HOSPITAL-BED-SATURATION.jpg?w=768&amp;quality=70 2x\" media=\"(min-width: 0)\"\/><img decoding=\"async\" src=\"https:\/\/www.capgemini.com\/no-no\/wp-content\/uploads\/2021\/09\/ÎÚÑ»´«Ã½_Client-Stories_ARS-DEVELOPS-STEP-TO-PREDICT-HOSPITAL-BED-SATURATION.jpg\" class=\"header-img header-img-d\" alt=\"\" style=\"object-fit:cover;object-position:44% 59%\" loading=\"eager\"\/><\/picture><\/div><div class=\"heroPictureCardHeaderShape\"><\/div><div class=\"container\"><div class=\"row\"><div class=\"col-md-12\"><div class=\"box\"><div class=\"boxTagWrapper\"><div class=\"tagInfo\"><div><span class=\"box-tag\">Client story<\/span><\/div><\/div><div class=\"brandInfo\"><div class=\"brandLogo\"><img decoding=\"async\" loading=\"lazy\" src=\"\/wp-content\/themes\/capgemini2020\/assets\/images\/capgemini-invent.svg\" alt=\"capgemini-invent\"\/><\/div><\/div><\/div><div class=\"box-title\"><h1 data-maxlength=\"34\">ARS develops STEP to predict hospital bed saturation<\/h1><\/div><div class=\"inner-row-insight download-btn\"><div class=\"col-md-4 downloadFiles addPadding\"><a class=\"button-download--small\" type=\"download\" href=\"https:\/\/www.capgemini.com\/no-no\/wp-content\/uploads\/2021\/12\/ASR-STEP-case-study.pdf\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"opens in a new window\"><span>Download client story<\/span><span class=\"type\">2 MB  pdf<\/span><\/a><\/div><\/div><\/div><div class=\"infoWrapper \"><div class=\"row\"><div class=\"col-md-4\"><span class=\"fieldName\">Client: ARS \u00cele-de-France<\/span><\/div><div class=\"col-md-4\"><span class=\"fieldName\">Region: France<\/span><\/div><div class=\"col-md-4\"><span class=\"fieldName\">Sector: Public Sector<\/span><\/div><\/div><\/div><\/div><\/div><\/div><\/header>\n\n\n\n<section class=\"wp-block-cg-blocks-intro-para undefined section section--intro\"><div class=\"intro-para\"><div class=\"container\"><div class=\"row\"><div class=\"col-12 col-md-1\"><nav class=\"article-social\"><ul class=\"social-nav\"><li class=\"ip-order-fb\"><a href=\"https:\/\/www.facebook.com\/sharer\/sharer.php?u=https:\/\/www.capgemini.com\/no-no\/news\/client-stories\/ars-develops-step-to-predict-hospital-bed-saturation\/\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"opens in a new window\"><i aria-hidden=\"true\" class=\"icon-fb\"><\/i><span class=\"sr-only\">Facebook<\/span><\/a><\/li><li class=\"ip-order-tw\"><a href=\"https:\/\/twitter.com\/intent\/tweet?url=https:\/\/www.capgemini.com\/no-no\/news\/client-stories\/ars-develops-step-to-predict-hospital-bed-saturation\/&amp;text=ARS develops STEP to predict hospital bed saturation\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"opens in a new window\"><i aria-hidden=\"true\" class=\"icon-tw\"><\/i><span class=\"sr-only\">Twitter<\/span><\/a><\/li><li class=\"ip-order-li\"><a href=\"https:\/\/www.linkedin.com\/sharing\/share-offsite\/?url=https:\/\/www.capgemini.com\/no-no\/news\/client-stories\/ars-develops-step-to-predict-hospital-bed-saturation\/&amp;text=ARS develops STEP to predict hospital bed saturation\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"opens in a new window\"><i aria-hidden=\"true\" class=\"icon-li\"><\/i><span class=\"sr-only\">Linkedin<\/span><\/a><\/li><\/ul><\/nav><\/div><div class=\"col-12 col-md-11 col-lg-10\"><h2 class=\"intro-para-title\">In partnership with ÎÚÑ»´«Ã½, ARS (Agence R\u00e9gionale de Sant\u00e9) Regional Health Agency has implemented an innovative tool to improve the management of hospital capacity in times of the COVID-19 pandemic and support decision-making in everyday health care<\/h2><p class=\"intro-para-content\"><strong>Client Challenge:<\/strong> ARS wanted to better manage bed capacity and balance scheduled and unscheduled care during periods of uncertainty such as the COVID-19 crisis<br><br><strong>Solution:<\/strong> Working with ÎÚÑ»´«Ã½ Invent, ARS has developed STEP, a predictive, decision-supportive, and policy impact evaluation tool that is used to monitor the COVID-19 bed capacity situation of hospitals in the region<\/p><\/div><\/div><\/div><\/div><\/section>\n\n\n\n<section class=\"wp-block-cg-blocks-group undefined section section--article-content section--story-content article-body\"><div class=\"article-main-content\"><div class=\"container\"><div class=\"row\"><div class=\"col-12 col-md-11 col-lg-10 offset-md-1 offset-lg-1\"><div class=\"article-text article-quote-text\">\n<h3 class=\"wp-block-heading\" id=\"h-striking-the-optimal-balance-between-scheduled-and-un-scheduled-care\">Striking the optimal balance between scheduled and un-scheduled care<\/h3>\n\n\n\n<p>Over the last two years, hospitals of the \u00cele-De-France Regional Health Agency (ARS) have struggled with trading-off between scheduled care, such as planned hospital procedures, and unscheduled emergencies directed to critical care units. As a completely new pathology, COVID-19 has increased the uncertainty as to how many programmed procedures can be rescheduled to accommodate the rise in unplanned hospital stays. Hence, striking an optimal balance between these two often equally urgent categories has become even more critical.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-monitoring-occupancy-levels-with-step\">Monitoring occupancy levels with STEP<\/h3>\n\n\n\n<p>In order to help healthcare providers treat many patients while maintaining occupancy levels below critical thresholds, ÎÚÑ»´«Ã½ Invent and ARS have developed STEP, the Saturation Bed Anticipation tool.<\/p>\n\n\n\n<p>STEP is an innovative predictive instrument designed to improve hospital capacity management at both regional and departmental levels by predicting the number of beds needed and hospital saturation. This included how many beds are available in critical care as well as for conventional hospitalization (medical and surgical). It also helps arbitrate between COVID- 19 and Non-COVID-19 beds while maintaining a minimum number of available beds for patients affected by the pandemic.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-step-use-cases\">STEP use cases<\/h3>\n\n\n\n<p>So far, ARS has applied STEP in a variety of ways. The solution has helped the agency to identify the departments and hospitals that are currently at risk of capacity oversaturation. In addition, ARS can now simulate future scenarios based on key parameters such as reproduction number, level of planned and unplanned activities, number of beds at the regional or department level, number of employees on holiday, and the impact of seasonal influenza. Finally, the organization uses STEP to analyze patient flow, detect possible discrepancies, and then share them with the parties involved.<\/p>\n\n\n\n<p>In this way, STEP enables decision-makers in the healthcare sector to have a clear vision on the current situation and capture both present and future epidemic trends. This in turn allows them to proactively respond to the COVID-19 crisis. At present, ARS and ÎÚÑ»´«Ã½ Invent are also working on a new feature of STEP that will assess the impact of public policy measures such as lockdowns and suggest ad-hoc strategies for reprogramming hospital activity.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-a-multidisciplinary-partnership-for-saving-lives\">A multidisciplinary partnership for saving lives<\/h3>\n\n\n\n<p>The STEP project connects people and expertise to navigate in complex ecosystems. In this partnership, everyone comes from a different background and offers insight from a variety of perspectives, such as from doctors, epidemiologists, consultants, and data scientists.<\/p>\n\n\n\n<p>Out of this joint effort, ARS and ÎÚÑ»´«Ã½ Invent have managed to delineate drivers for decision-makers, allocate the most adequate level of resources, and provide the right amount of effort. STEP enables doctors and nurses to plan ahead and be there at the right moment, saving not only time and energies but possibly also lives.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/section>\n","protected":false},"excerpt":{"rendered":"<p>In partnership with ÎÚÑ»´«Ã½, ARS Regional Health Agency has implemented an innovative tool to support decision-making in everyday health 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